The answer is that Azure AI Vision’s OCR feature extracts printed and handwritten text from images and documents. This is correct because the service uses deep learning models trained to recognize characters and words from diverse visual sources—like scanned PDFs, photos of signs, or handwritten notes—and converts that visual text into machine-readable data, enabling downstream tasks such as search, indexing, or analysis. On the AI-900 exam, this question tests your understanding of Azure AI Vision’s core capabilities within the Computer Vision workload; a common trap is confusing OCR with other features like image classification or object detection, which identify objects or scenes rather than reading text. To remember, think of OCR as “reading the words on the page,” not just recognizing what the page shows. A simple memory tip: OCR = Optical Character Reading, where the “R” stands for “reading” text, not just recognizing objects.
AI-900 Practice Question: Describe features of computer vision workloads on Azure
This AI-900 practice question tests your understanding of describe features of computer vision workloads on azure. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
What does Azure AI Vision's 'optical character recognition' (OCR) feature do?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Extracts printed and handwritten text from images and documents
Azure AI Vision's OCR feature is designed to extract printed and handwritten text from images and documents, converting visual text into machine-readable data. This is correct because OCR uses deep learning models to detect and read text characters from various visual sources, enabling downstream processing like search or analysis.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Converts text files into images for archival purposes
Why it's wrong here
Text-to-image conversion is image rendering — OCR does the reverse: extracts text from images.
✓
Extracts printed and handwritten text from images and documents
Why this is correct
OCR reads text from photos and scanned documents — enabling digitisation of printed/handwritten content for further processing.
Related concept
Read the scenario before looking for a memorised answer.
✗
Recognises optical fibre cables in data centre photographs
Why it's wrong here
This is a joke — OCR stands for Optical Character Recognition, which extracts text from images.
✗
Corrects spelling errors in text extracted from forms
Why it's wrong here
Spell checking is text post-processing — OCR's job is to extract the text from images accurately.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse OCR with other computer vision tasks like object detection (Option C) or assume OCR includes post-processing like spell checking (Option D), when in fact OCR is strictly about text extraction from visual media.
Detailed technical explanation
How to think about this question
Under the hood, Azure AI Vision's OCR leverages a combination of convolutional neural networks (CNNs) for feature extraction and recurrent neural networks (RNNs) with connectionist temporal classification (CTC) for sequence recognition. It supports both printed text (including multiple languages) and handwritten text, and can handle varied orientations and lighting conditions. A real-world scenario is automated invoice processing, where OCR extracts key fields like invoice numbers and dates from scanned documents for entry into accounting systems.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this AI-900 question in full detail.
Describe features of computer vision workloads on Azure — This question tests Describe features of computer vision workloads on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Extracts printed and handwritten text from images and documents — Azure AI Vision's OCR feature is designed to extract printed and handwritten text from images and documents, converting visual text into machine-readable data. This is correct because OCR uses deep learning models to detect and read text characters from various visual sources, enabling downstream processing like search or analysis.
What should I do if I get this AI-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Variation 1. What is Optical Character Recognition (OCR) and which Azure AI service provides it?
medium
A.Speech recognition; provided by Azure AI Speech
✓ B.Technology that extracts text from images; provided by Azure AI Vision
C.Language translation; provided by Azure AI Translator
D.Handwriting analysis for personality assessment; provided by Azure AI Face
Why B: Optical Character Recognition (OCR) is the technology that extracts printed or handwritten text from images, such as scanned documents or photos, and converts it into machine-readable text. This capability is provided by the Azure AI Vision service, specifically through its Read API, which can process both printed and handwritten text from a variety of image formats.
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Question Discussion
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